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<a href="_abstract_loss_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       super class of all loss functions</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * </span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> *</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \author      T. Glasmachers</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \date        2010-2011</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> * \file</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> *</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * </span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * </span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * </span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * </span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> *</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> */</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span> </div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="preprocessor">#ifndef SHARK_OBJECTIVEFUNCTIONS_LOSS_ABSTRACTLOSS_H</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#define SHARK_OBJECTIVEFUNCTIONS_LOSS_ABSTRACTLOSS_H</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span> </div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_cost_8h.html" title="cost function for quantitative judgement of deviations of predictions from target values">shark/ObjectiveFunctions/AbstractCost.h</a>&gt;</span></div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;<a class="code" href="_base_8h.html">shark/LinAlg/Base.h</a>&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="preprocessor">#include &lt;<a class="code" href="_proxy_reference_traits_8h.html">shark/Core/Traits/ProxyReferenceTraits.h</a>&gt;</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span>    <span class="comment"></span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="comment">/// \defgroup lossfunctions Loss Functions</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="comment">/// \brief Loss functions define loss values between a model prediction and a given label.</span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="comment"></span><span class="comment"></span> </div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="comment">/// \brief Loss function interface</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment">///</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment">/// In statistics and machine learning, a loss function encodes</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">/// the severity of getting a label wrong. This is am important</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment">/// special case of a cost function (see AbstractCost), where</span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span><span class="comment">/// the cost is computed as the average loss over a set, also</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="comment">/// known as (empirical) risk.</span></div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="comment">///</span></div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment">/// It is generally agreed that loss values are non-negative,</span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">/// and that the loss of correct prediction is zero. This rule</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">/// is not formally checked, but instead left to the various</span></div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment">/// sub-classes.</span></div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment">///</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">/// \ingroup lossfunctions</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> LabelT, <span class="keyword">class</span> OutputT = LabelT&gt;</div>
<div class="foldopen" id="foldopen00062" data-start="{" data-end="};">
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html">   62</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">AbstractLoss</a> : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_cost.html" title="Cost function interface.">AbstractCost</a>&lt;LabelT, OutputT&gt;</div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span>{</div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_cost.html" title="Cost function interface.">AbstractCost&lt;LabelT, OutputT&gt;</a> <a class="code hl_class" href="classshark_1_1_abstract_cost.html" title="Cost function interface.">base_type</a>;</div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#aff632efe5055d1f07de94a790b222b85">   66</a></span>    <span class="keyword">typedef</span> OutputT <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#aff632efe5055d1f07de94a790b222b85">OutputType</a>;</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a1a5e866edf2da03bb50778d2271c01da">   67</a></span>    <span class="keyword">typedef</span> LabelT <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a1a5e866edf2da03bb50778d2271c01da">LabelType</a>;</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a87fa1fa41bb3c1d5ce75137428724536">   68</a></span>    <span class="keyword">typedef</span> RealMatrix <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a87fa1fa41bb3c1d5ce75137428724536">MatrixType</a>;</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span> </div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">   70</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;OutputType&gt;::type</a> <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a>;</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">   71</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;LabelType&gt;::type</a> <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">BatchLabelType</a>;</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span><span class="comment"></span> </div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span><span class="comment">    /// \brief Const references to LabelType</span></div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#ac52e23c4acfdb2d08b55420101eee787">   74</a></span><span class="comment"></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> ConstProxyReference&lt;LabelType const&gt;::type <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac52e23c4acfdb2d08b55420101eee787" title="Const references to LabelType.">ConstLabelReference</a>;<span class="comment"></span></div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span><span class="comment">    /// \brief Const references to OutputType</span></div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a50b1635725e3a6bbb6017a6e3c4a52ca">   76</a></span><span class="comment"></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> ConstProxyReference&lt;OutputType const&gt;::type <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a50b1635725e3a6bbb6017a6e3c4a52ca" title="Const references to OutputType.">ConstOutputReference</a>;</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span> </div>
<div class="foldopen" id="foldopen00078" data-start="{" data-end="}">
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#aae8049c358e6ccfece94d4a978306c4c">   78</a></span>    <a class="code hl_function" href="classshark_1_1_abstract_loss.html#aae8049c358e6ccfece94d4a978306c4c">AbstractLoss</a>(){</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>        this-&gt;<a class="code hl_variable" href="classshark_1_1_abstract_cost.html#a97902a8a75733642a4472b463ae9b7dc">m_features</a> |= <a class="code hl_enumvalue" href="classshark_1_1_abstract_cost.html#a3f2ae17818520465f0e73257fd202bacaaa945f1c8fb58952a4dbea1a1ff86231">base_type::IS_LOSS_FUNCTION</a>;</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>    }</div>
</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span><span class="comment"></span> </div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span><span class="comment">    /// \brief evaluate the loss for a batch of targets and a prediction</span></div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span><span class="comment">    /// \param  target      target values</span></div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span><span class="comment">    /// \param  prediction  predictions, typically made by a model</span></div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8">   86</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">eval</a>( BatchLabelType <span class="keyword">const</span>&amp; target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a> <span class="keyword">const</span>&amp; prediction) <span class="keyword">const</span> = 0;</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span><span class="comment"></span> </div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span><span class="comment">    /// \brief evaluate the loss for a target and a prediction</span></div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span><span class="comment">    /// \param  target      target value</span></div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span><span class="comment">    /// \param  prediction  prediction, typically made by a model</span></div>
<div class="foldopen" id="foldopen00092" data-start="{" data-end="}">
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a26f69483e0f62462bbc45e2734f65a4b">   92</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a26f69483e0f62462bbc45e2734f65a4b" title="evaluate the loss for a target and a prediction">eval</a>( <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac52e23c4acfdb2d08b55420101eee787" title="Const references to LabelType.">ConstLabelReference</a> target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a50b1635725e3a6bbb6017a6e3c4a52ca" title="Const references to OutputType.">ConstOutputReference</a> prediction)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">BatchLabelType</a> labelBatch = <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;LabelType&gt;::createBatch</a>(target,1);</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>        <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(labelBatch,0)=target;</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a> predictionBatch = <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;OutputType&gt;::createBatch</a>(prediction,1);</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>        <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(predictionBatch,0)=prediction;</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">eval</a>(labelBatch,predictionBatch);</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>    }</div>
</div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span><span class="comment"></span> </div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span><span class="comment">    /// \brief evaluate the loss and its derivative for a target and a prediction</span></div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span><span class="comment">    /// \param  target      target value</span></div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span><span class="comment">    /// \param  prediction  prediction, typically made by a model</span></div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span><span class="comment">    /// \param  gradient    the gradient of the loss function with respect to the prediction</span></div>
<div class="foldopen" id="foldopen00105" data-start="{" data-end="}">
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a71706ed4c40d1635db1c372ecf5c8686">  105</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a71706ed4c40d1635db1c372ecf5c8686" title="evaluate the loss and its derivative for a target and a prediction">evalDerivative</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac52e23c4acfdb2d08b55420101eee787" title="Const references to LabelType.">ConstLabelReference</a> target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a50b1635725e3a6bbb6017a6e3c4a52ca" title="Const references to OutputType.">ConstOutputReference</a> prediction, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#aff632efe5055d1f07de94a790b222b85">OutputType</a>&amp; gradient)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">BatchLabelType</a> labelBatch = <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;LabelType&gt;::createBatch</a>(target,1);</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>        <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(labelBatch, 0) = target;</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a> predictionBatch = <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;OutputType&gt;::createBatch</a>(prediction, 1);</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>        <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(predictionBatch, 0) = prediction;</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a> gradientBatch = <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;OutputType&gt;::createBatch</a>(gradient, 1);</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>        <span class="keywordtype">double</span> ret = <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a71706ed4c40d1635db1c372ecf5c8686" title="evaluate the loss and its derivative for a target and a prediction">evalDerivative</a>(labelBatch, predictionBatch, gradientBatch);</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>        gradient = <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(gradientBatch, 0);</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>        <span class="keywordflow">return</span> ret;</div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span>    }</div>
</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>    <span class="comment"></span></div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span><span class="comment">    /// \brief evaluate the loss and its first and second derivative for a target and a prediction</span></div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span><span class="comment">    /// \param  target      target value</span></div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span><span class="comment">    /// \param  prediction  prediction, typically made by a model</span></div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span><span class="comment">    /// \param  gradient    the gradient of the loss function with respect to the prediction</span></div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span><span class="comment">    /// \param  hessian     the hessian of the loss function with respect to the prediction</span></div>
<div class="foldopen" id="foldopen00122" data-start="{" data-end="}">
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a7bde41258ced1db72e467f26d2439d0c">  122</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a7bde41258ced1db72e467f26d2439d0c" title="evaluate the loss and its first and second derivative for a target and a prediction">evalDerivative</a>(</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac52e23c4acfdb2d08b55420101eee787" title="Const references to LabelType.">ConstLabelReference</a> target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a50b1635725e3a6bbb6017a6e3c4a52ca" title="Const references to OutputType.">ConstOutputReference</a> prediction,</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#aff632efe5055d1f07de94a790b222b85">OutputType</a>&amp; gradient,<a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a87fa1fa41bb3c1d5ce75137428724536">MatrixType</a> &amp; hessian</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>    )<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>        <a class="code hl_define" href="_flags_8h.html#aabce93ad7a4ffa638fa51321701ad1aa">SHARK_FEATURE_EXCEPTION_DERIVED</a>(<a class="code hl_enumvalue" href="classshark_1_1_abstract_cost.html#a3f2ae17818520465f0e73257fd202baca757525584b3fc0a7aa977255fd6d8232">HAS_SECOND_DERIVATIVE</a>);</div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>        <span class="keywordflow">return</span> 0.0;  <span class="comment">// dead code, prevent warning</span></div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>    }</div>
</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span><span class="comment"></span> </div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span><span class="comment">    /// \brief evaluate the loss and the derivative w.r.t. the prediction</span></div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span><span class="comment">    /// \par</span></div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span><span class="comment">    /// The default implementations throws an exception.</span></div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span><span class="comment">    /// If you overwrite this method, don&#39;t forget to set</span></div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span><span class="comment">    /// the flag HAS_FIRST_DERIVATIVE.</span></div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="comment">    /// \param  target      target value</span></div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span><span class="comment">    /// \param  prediction  prediction, typically made by a model</span></div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span><span class="comment">    /// \param  gradient    the gradient of the loss function with respect to the prediction</span></div>
<div class="foldopen" id="foldopen00139" data-start="{" data-end="}">
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#aaff8e4357ab4257d46025368575aac15">  139</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#aaff8e4357ab4257d46025368575aac15" title="evaluate the loss and the derivative w.r.t. the prediction">evalDerivative</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">BatchLabelType</a> <span class="keyword">const</span>&amp; target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a> <span class="keyword">const</span>&amp; prediction, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a>&amp; gradient)<span class="keyword"> const</span></div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span><span class="keyword">    </span>{</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>        <a class="code hl_define" href="_flags_8h.html#aabce93ad7a4ffa638fa51321701ad1aa">SHARK_FEATURE_EXCEPTION_DERIVED</a>(<a class="code hl_enumvalue" href="classshark_1_1_abstract_cost.html#a3f2ae17818520465f0e73257fd202bacad1e0927ebd68caf428c52cc4cecc084a">HAS_FIRST_DERIVATIVE</a>);</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>        <span class="keywordflow">return</span> 0.0;  <span class="comment">// dead code, prevent warning</span></div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>    }</div>
</div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>    <span class="comment"></span></div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span><span class="comment">    /// from AbstractCost</span></div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span><span class="comment">    /// \param  targets      target values</span></div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span><span class="comment">    /// \param  predictions  predictions, typically made by a model</span></div>
<div class="foldopen" id="foldopen00149" data-start="{" data-end="}">
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a0d53dd678d58b2cb3a213cdc829937da">  149</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a0d53dd678d58b2cb3a213cdc829937da">eval</a>(<a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;LabelType&gt;</a> <span class="keyword">const</span>&amp; targets, <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;OutputType&gt;</a> <span class="keyword">const</span>&amp; predictions)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(predictions.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>() == targets.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>());</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(predictions.<a class="code hl_function" href="group__shark__globals.html#gabd82edf467b9b82f4b0a1e70fd695311" title="Returns the number of batches of the set.">numberOfBatches</a>() == targets.<a class="code hl_function" href="group__shark__globals.html#gabd82edf467b9b82f4b0a1e70fd695311" title="Returns the number of batches of the set.">numberOfBatches</a>());</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>        <span class="keywordtype">int</span> numBatches = (int) targets.<a class="code hl_function" href="group__shark__globals.html#gabd82edf467b9b82f4b0a1e70fd695311" title="Returns the number of batches of the set.">numberOfBatches</a>();</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span>        <span class="keywordtype">double</span> error = 0;</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>        <a class="code hl_define" href="_open_m_p_8h.html#a8a63d79e2c3625260e6092d933f21a98" title="Set of macros to help usage of OpenMP with Shark.">SHARK_PARALLEL_FOR</a>(<span class="keywordtype">int</span> i = 0; i &lt; numBatches; ++i){</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>            <span class="keywordtype">double</span> batchError= <a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">eval</a>(targets.<a class="code hl_function" href="group__shark__globals.html#ga73034ee5639176b0d45e1059859d0f0a">batch</a>(i),predictions.<a class="code hl_function" href="group__shark__globals.html#ga73034ee5639176b0d45e1059859d0f0a">batch</a>(i));</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>            <a class="code hl_define" href="_open_m_p_8h.html#a6de33df9d72bea69f903cffb391e7121">SHARK_CRITICAL_REGION</a>{</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>                error+=batchError;</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>            }</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>        }</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span>        <span class="keywordflow">return</span> error / targets.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>    }</div>
</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span><span class="comment"></span> </div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span><span class="comment">    /// \brief evaluate the loss for a target and a prediction</span></div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span><span class="comment">    /// \par</span></div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span><span class="comment">    /// convenience operator</span></div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span><span class="comment">    /// \param  target      target value</span></div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span><span class="comment">    /// \param  prediction  prediction, typically made by a model</span></div>
<div class="foldopen" id="foldopen00170" data-start="{" data-end="}">
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#a235a058270db9218fd889391d0385047">  170</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a235a058270db9218fd889391d0385047" title="evaluate the loss for a target and a prediction">operator () </a>(<a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a1a5e866edf2da03bb50778d2271c01da">LabelType</a> <span class="keyword">const</span>&amp; target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#aff632efe5055d1f07de94a790b222b85">OutputType</a> <span class="keyword">const</span>&amp; prediction)<span class="keyword"> const</span></div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span><span class="keyword">    </span>{ <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">eval</a>(target, prediction); }</div>
</div>
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno">  172</span> </div>
<div class="foldopen" id="foldopen00173" data-start="{" data-end="}">
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_loss.html#ad232712edcc7a2df8bf2bc4936ae93f9">  173</a></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#a235a058270db9218fd889391d0385047" title="evaluate the loss for a target and a prediction">operator () </a>(<a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">BatchLabelType</a> <span class="keyword">const</span>&amp; target, <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">BatchOutputType</a> <span class="keyword">const</span>&amp; prediction)<span class="keyword"> const</span></div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span><span class="keyword">    </span>{ <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">eval</a>(target, prediction); }</div>
</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span> </div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span>    <span class="keyword">using </span>base_type::operator();</div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span>};</div>
</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span> </div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span> </div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>}</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span><span class="preprocessor">#endif</span></div>
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